code: def map_dense(f, xs, pos_args):
      pytrees = []
      for inp in _unstack_pytree(xs):
          pytrees.append(f(*inp, *pos_args))
      return _stack_pytree(pytrees)
  
imports: from contextlib import nullcontext
  import torch
  import torch.utils._pytree
  from torch._C import DispatchKey
  from torch._dispatch.python import suspend_functionalization
  from torch._functorch.aot_autograd import AOTConfig, create_joint, from_fun
  from torch._higher_order_ops.cond import _has_potential_branch_input_alias, _has_potential_branch_input_mutation, UnsupportedAliasMutationException
  from torch._ops import HigherOrderOperator
  from torch._subclasses.fake_tensor import FakeTensorMode
  from torch._subclasses.functional_tensor import FunctionalTensor, FunctionalTensorMode, unset_functional_temporarily
  from torch.fx.experimental.proxy_tensor import disable_proxy_modes_tracing, make_fx, ProxyTorchDispatchMode, track_tensor_tree
  from torch.multiprocessing.reductions import StorageWeakRef
label_desc: Use image node_id 6 for calling a global function with example usage: map_dense(f, xs, pos_args) and returns: _stack_pytree